Secure AI interactions and environments with Microsoft Purview
At a glance
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Subject
AI tools such as Microsoft Copilot and custom AI apps can access and generate sensitive content across your organization. You learn how to:
- Apply sensitivity labels and data loss prevention policies so AI respects existing protections.
- Use Data Security Posture Management for AI and auditing tools to discover and investigate AI-related risks.
- Apply eDiscovery and Communication Compliance to manage content generated by AI.
- Use Insider Risk Management and Adaptive Protection to respond to risky behavior and reduce oversharing.
Prerequisites
- Foundational knowledge of Microsoft security and compliance
- Basic familiarity with Microsoft Purview features such as sensitivity labels, data loss prevention, and retention
- Awareness of Microsoft Entra concepts and how Microsoft 365 Copilot accesses data
Achievement Code
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Modules in this learning path
Microsoft Purview helps organizations assess how Microsoft 365 Copilot and other AI tools interact with sensitive data. Using Data Security Posture Management (DSPM) for AI, organizations can evaluate exposure risks, understand which AI tools are in use, and identify how sensitive data is accessed during AI interactions. Audit provides visibility into specific Copilot prompts and responses for compliance and investigation scenarios.
AI tools like Microsoft 365 Copilot create new ways to interact with sensitive data, but they also introduce new risks. Learn how Microsoft Purview helps you apply security and compliance controls that protect data, manage AI activity, and support responsible use at scale.
AI tools across enterprise and public environments create new opportunities but also introduce data security and compliance risks. Microsoft Purview helps reduce these risks by discovering AI usage, assessing compliance needs, and applying integrated controls for protection, retention, and responsible use.
Microsoft Purview provides tools to secure developer AI environments by discovering apps, assessing data access, and applying appropriate protections. This includes detecting generative AI usage, assigning user risk levels, and applying dynamic enforcement based on user behavior and data sensitivity.